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A national experiment reveals where a growth mindset improves achievement

A global priority for the behavioural sciences is to develop cost-effective, scalable interventions that could improve the academic outcomes of adolescents at a population level, but no such interventions have so far been evaluated in a population-generalizable sample. Here we show that a short (les...

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Detalles Bibliográficos
Autores principales: Yeager, David S., Hanselman, Paul, Walton, Gregory M., Murray, Jared S., Crosnoe, Robert, Muller, Chandra, Tipton, Elizabeth, Schneider, Barbara, Hulleman, Chris S., Hinojosa, Cintia P., Paunesku, David, Romero, Carissa, Flint, Kate, Roberts, Alice, Trott, Jill, Iachan, Ronaldo, Buontempo, Jenny, Yang, Sophia Man, Carvalho, Carlos M., Hahn, P. Richard, Gopalan, Maithreyi, Mhatre, Pratik, Ferguson, Ronald, Duckworth, Angela L., Dweck, Carol S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6786290/
https://www.ncbi.nlm.nih.gov/pubmed/31391586
http://dx.doi.org/10.1038/s41586-019-1466-y
Descripción
Sumario:A global priority for the behavioural sciences is to develop cost-effective, scalable interventions that could improve the academic outcomes of adolescents at a population level, but no such interventions have so far been evaluated in a population-generalizable sample. Here we show that a short (less than one hour), online growth mindset intervention—which teaches that intellectual abilities can be developed—improved grades among lower-achieving students and increased overall enrolment to advanced mathematics courses in a nationally representative sample of students in secondary education in the United States. Notably, the study identified school contexts that sustained the effects of the growth mindset intervention: the intervention changed grades when peer norms aligned with the messages of the intervention. Confidence in the conclusions of this study comes from independent data collection and processing, pre-registration of analyses, and corroboration of results by a blinded Bayesian analysis.